Spatial sampling uncertainty in SMEX04 soil moisture fields: A data-based resampling experiment

A data-based resampling experiment is performed to estimate sampling errors of area-averaged soil moisture estimates due to spatial sampling by ground-based sensors. The data consists of high-resolution soil moisture images derived from the Polarimetric Scanning Radiometer (PSR/CX) sensor flown on an aircraft as part of the summer field experiment (SMEX04 — Soil Moisture Experiment 2004) in the monsoon region of Sonora, Mexico. The sampling characteristics are investigated by accounting for random networks and evenly spaced networks. For random network designs, we develop a simple model that can be used to estimate the sampling uncertainty (expressed as standard deviation of sampling error as a percentage of the areal mean soil moisture) as a function of the number of sensors, mean soil moisture content and averaging area. This model is valid for five or more sensors. The model should prove useful to those wishing to assess the area-averaged performance of a soil moisture network. Furthermore, the method of analysis is applicable to other study regions (Oklahoma, Iowa, Alabama, Georgia, and Arizona) where soil moisture fields have been mapped at high resolution using airborne passive microwave remote sensors.